Dynamic Link Recommendation Based on Anonymous Weblog Mining


The KIPS Transactions:PartC, Vol. 10, No. 5, pp. 647-656, Oct. 2003
10.3745/KIPSTC.2003.10.5.647,   PDF Download:

Abstract

In Webspace, mining traversal patterns is to understand user’s path traversal patterns. On this mining, it has a unique characteristic which objects (for example, URLs) may be visited due to their positions rather than contents, because users move to other objects according to providing information services. As a consequence, it becomes very complex to extract meaningful information from these data. Recently discovering traversal patterns has been an important problem in data mining because there has been an increasing amount of research activity on various aspects of improving the quality of information services. This paper presents a Dynamic Link Recommendation (DLR) algorithm that recommends link sets on a Web site through mining frequent traversal patterns. It can be employed to any Web site with massive amounts of data. Our experimentation with two real Weblog data clearly validate that our method outperforms traditional method.


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Cite this article
[IEEE Style]
Y. S. Hui and O. H. Seog, "Dynamic Link Recommendation Based on Anonymous Weblog Mining," The KIPS Transactions:PartC, vol. 10, no. 5, pp. 647-656, 2003. DOI: 10.3745/KIPSTC.2003.10.5.647.

[ACM Style]
Yun Seon Hui and O Hae Seog. 2003. Dynamic Link Recommendation Based on Anonymous Weblog Mining. The KIPS Transactions:PartC, 10, 5, (2003), 647-656. DOI: 10.3745/KIPSTC.2003.10.5.647.